In the near future, humans and robots are expected to perform collaborative tasks involving physical interaction in various environments, such as homes, hospitals, and factories. Robots are good at precision, strength, and repetition, while humans are better at cognitive tasks. The concept, known as physical human-robot interaction (pHRI), takes advantage of these abilities and is highly beneficial by bringing speed, flexibility, and ergonomics to the execution of complex tasks. Current research in pHRI focuses on designing controllers and developing new methods which offer a better tradeoff between robust stability and high interaction performance. In this paper, we propose a new controller, fractional order admittance controller, for pHRI systems. The stability and transparency analyses of the new control system are performed computationally with human-in-the-loop. Impedance matching is proposed to map fractional order control parameters to integer order ones, and then the stability robustness of the system is studied analytically. Furthermore, the interaction performance is investigated experimentally through two human subject studies involving continuous contact with linear and nonlinear viscoelastic environments. The results indicate that the fractional order admittance controller can be made more robust and transparent than the integer order admittance controller and the use of fractional order term can reduce the human effort during tasks involving contact interactions with environment.
In today's automation driven manufacturing environments, emerging technologies like cobots (collaborative robots) and augmented reality interfaces can help integrating humans into the production workflow to benefit from their adaptability and cognitive skills. In such settings, humans are expected to work with robots side by side and physically interact with them. However, the trade-off between stability and transparency is a core challenge in the presence of physical human robot interaction (pHRI). While stability is of utmost importance for safety, transparency is required for fully exploiting the precision and ability of robots in handling labor intensive tasks. In this work, we propose a new variable admittance controller based on fractional order control to handle this tradeoff more effectively. We compared the performance of fractional order variable admittance controller with a classical admittance controller with fixed parameters as a baseline and an integer order variable admittance controller during a realistic drilling task. Our comparisons indicate that the proposed controller led to a more transparent interaction compared to the other controllers without sacrificing the stability. We also demonstrate a use case for an augmented reality (AR) headset which can augment human sensory capabilities for reaching a certain drilling depth otherwise not possible without changing the role of the robot as the decision maker.
Abstract-In physical human-robot interaction (pHRI), the cognitive skill of a human is combined with the accuracy, repeatability and strength of a robot. While the promises and potential outcomes of pHRI are glamorous, the control of such coupled systems is challenging in many aspects. In this paper, we propose a new controller, fractional order admittance controller, for pHRI systems. The stability analysis of the new control system with human in-the-loop is performed and the interaction performance is investigated experimentally with 10 subjects during a task imitating a contact with a stiff environment. The results show that the fractional order controller is more robust than the standard admittance controller and helps to reduce the human effort in task execution.
This paper reports on a study which designed and developed a multi-fingered haptic interface in conjunction with a three-dimensional (3D) virtual model of a section of the cell membrane in order to enable students to work collaboratively to learn cell biology. Furthermore, the study investigated whether the addition of haptic feedback to the 3D virtual reality (VR) simulation affected learning of key concepts in nanoscale cell biology for students aged 12 to 13. The haptic interface was designed so that the haptic feedback could be turned on or switched off. Students (N = 64), in two secondary schools, worked in pairs, on activities designed to support learning of specific difficult concepts. Findings from observation of the activities and interviews revealed that students believed that being immersed in the 3D VR environment and being able to feel structures and movements within the model and work collaboratively assisted their learning. More specifically, the pilot/co-pilot model that we developed was successful for enabling collaborative learning and reducing the isolating effects of immersion with a 3D headset. Results of pre and post-tests of conceptual knowledge showed significant knowledge gains but addition of haptic feedback did not affect the knowledge gains significantly. The study enabled identification of important issues to consider when designing and using haptic-enabled 3D VR environments for collaborative learning.
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